AI governance frameworks in Prompt Engineering / GenAI - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is an AI governance framework?

An AI governance framework is a set of rules and guidelines that help organizations use AI responsibly and safely. It ensures AI systems are fair, transparent, and respect privacy.

beginner

Name one key principle commonly found in AI governance frameworks.

One key principle is transparency, which means making AI decisions understandable to people affected by them.

beginner

Why is fairness important in AI governance?

Fairness ensures AI does not treat people unfairly based on race, gender, or other personal traits. It helps avoid bias and discrimination.

intermediate

How does accountability fit into AI governance frameworks?

Accountability means someone is responsible for the AI system’s actions and outcomes. It helps fix problems and improve trust.

beginner

What role does privacy play in AI governance?

Privacy protects personal data used by AI. Governance frameworks require data to be handled carefully to keep people’s information safe.

Which of the following is NOT a common principle in AI governance frameworks?

A Unlimited data sharing

B Transparency

C Fairness

D Accountability

Unlimited data sharing is not a principle; AI governance frameworks emphasize protecting data privacy.

What does transparency in AI governance mean?

A Sharing all data publicly

B Hiding how AI works

C Ignoring AI errors

D Making AI decisions understandable

Transparency means making AI decisions clear and understandable to users.

Who should be accountable for AI system outcomes?

A No one

B Only the AI system itself

C The people or organizations deploying AI

D The users of AI only

Organizations deploying AI must take responsibility for its outcomes.

Why is fairness important in AI governance?

A To avoid bias and discrimination

B To increase profits only

C To make AI faster

D To reduce transparency

Fairness helps prevent AI from treating people unfairly based on personal traits.

What does AI governance require regarding personal data?

A Use data without consent

B Protect data privacy

C Share data with everyone

D Ignore data security

AI governance frameworks require protecting personal data privacy.

Explain the main goals of AI governance frameworks and why they matter.

Think about how AI affects people and what rules help keep it safe and fair.

Describe how accountability and transparency work together in AI governance.

Consider who answers for AI actions and how people know what AI does.

Practice

1. What is the main purpose of an AI governance framework?

easy

A. To increase the speed of AI model training

B. To improve the graphical user interface of AI apps

C. To reduce the cost of AI hardware

D. To guide safe and fair use of AI systems

Solution

1. Step 1: Understand the role of AI governance frameworks

   AI governance frameworks are designed to ensure AI is used responsibly and ethically.

2. Step 2: Identify the main goal

   The main goal is to guide safe and fair use, preventing harm and building trust.

3. Final Answer:

   To guide safe and fair use of AI systems -> Option D

4. Quick Check:

   Purpose of AI governance = safe and fair use [OK]

Hint: Focus on safety and fairness in AI use [OK]

Common Mistakes:

• Confusing governance with technical optimization
• Thinking governance is about cost or speed
• Ignoring ethical and safety aspects

2. Which of the following is a correct component of an AI governance framework?

easy

A. Faster GPU hardware

B. Policies and processes for AI use

C. New programming languages

D. User interface design templates

Solution

1. Step 1: Recall components of AI governance frameworks

   They include principles, policies, processes, roles, and tools to manage AI responsibly.

2. Step 2: Match options to components

   Only policies and processes relate directly to governance frameworks.

3. Final Answer:

   Policies and processes for AI use -> Option B

4. Quick Check:

   Governance components = policies and processes [OK]

Hint: Look for management and rules, not tech specs [OK]

Common Mistakes:

• Choosing hardware or software unrelated to governance
• Confusing governance with development tools
• Ignoring the role of policies

3. Consider this code snippet representing a simple AI governance check in Python:

def check_fairness(data):
    if 'bias' in data:
        return 'Unfair AI detected'
    else:
        return 'AI is fair'

result = check_fairness(['accuracy', 'bias'])
print(result)

What will be the output?

medium

A. Unfair AI detected

B. Error: 'bias' not defined

C. AI is fair

D. None

Solution

1. Step 1: Analyze the function logic

   The function checks if the string 'bias' is in the input list. If yes, it returns 'Unfair AI detected'.

2. Step 2: Check the input data

   The input list contains 'accuracy' and 'bias', so 'bias' is present.

3. Final Answer:

   Unfair AI detected -> Option A

4. Quick Check:

   Presence of 'bias' triggers unfair AI message [OK]

Hint: Check if 'bias' is in the list to decide output [OK]

Common Mistakes:

• Assuming 'bias' is a variable, not a string
• Ignoring the if condition logic
• Thinking the function returns None

4. The following code is intended to check if an AI model meets governance standards by verifying if it has a 'transparency' attribute. Identify the error:

class AIModel:
    def __init__(self, transparency):
        self.transparency = transparency

def check_governance(model):
    if model.transparency == True:
        return 'Governance passed'
    else:
        return 'Governance failed'

model = AIModel('yes')
print(check_governance(model))

medium

A. The transparency attribute should be a boolean, not a string

B. The method check_governance is missing a return statement

C. The class AIModel lacks a constructor

D. The print statement is outside the function

Solution

1. Step 1: Understand the attribute type check

   The function compares model.transparency to True (boolean).

2. Step 2: Check the attribute value in the instance

   The model is created with 'yes' (string), not True (boolean), so the condition fails.

3. Final Answer:

   The transparency attribute should be a boolean, not a string -> Option A

4. Quick Check:

   Type mismatch causes governance check failure [OK]

Hint: Match attribute types with condition checks [OK]

Common Mistakes:

• Ignoring type mismatch between string and boolean
• Thinking missing return causes error here
• Confusing class constructor presence

5. You are designing an AI governance framework for a healthcare AI system. Which combination of components best ensures ethical use and accountability?

hard

A. High accuracy metrics, cloud deployment, and automated updates

B. Faster model training, open-source code, and user-friendly UI

C. Clear policies, regular audits, and defined roles for oversight

D. Large datasets, complex algorithms, and minimal documentation

Solution

1. Step 1: Identify key governance needs in healthcare AI

   Ethical use and accountability require clear rules, monitoring, and responsible roles.

2. Step 2: Evaluate options for governance components

   Only Clear policies, regular audits, and defined roles for oversight includes policies, audits, and roles which align with governance goals.

3. Final Answer:

   Clear policies, regular audits, and defined roles for oversight -> Option C

4. Quick Check:

   Governance needs policies + audits + roles [OK]

Hint: Governance = policies + audits + roles, not tech features [OK]

Common Mistakes:

• Confusing governance with technical performance
• Ignoring the need for oversight roles
• Choosing options focused on speed or complexity